title: Nonlocal denoising using anisotropic structure tensor for 3D MRI.
abstract: OBJECTIVE
  Noise in magnetic resonance imaging (MRI) data is widely recognized to be harmful to image processing and subsequent quantitative analysis. To ameliorate the effects of image noise, the authors present a structure-tensor based nonlocal mean (NLM) denoising technique that can effectively reduce noise in MRI data and improve tissue characterization.
  
  
  METHODS
  The proposed 3D NLM algorithm uses a structure tensor to characterize information around tissue boundaries. The similarity weight of a pixel (or patch), which determines its contribution to the denoising process, is determined by the intensity and structure tensor simultaneously. Meanwhile, similarity of structure tensors is computed using an affine-invariant Riemannian metrics, which compares tensor properties more comprehensively and avoids orientation inaccuracy of structure subsequently. The proposed method is further extended for denoising high dimensional MRI data such as diffusion weighted MRI. It is also extended to handle Rician noise corruption so that denoising effects are further enhanced.
  
  
  RESULTS
  The proposed method was implemented in both simulated datasets and multiply modalities of real 3D MRI datasets. Comparisons with related state-of-the-art algorithms demonstrated that this method improves denoising performance qualitatively and quantitatively.
  
  
  CONCLUSIONS
  In this paper, high order structure information of 3D MRI was characterized by 3D structure tensor and compared for NLM denoising in a Riemannian space. Experiments with simulated and real human MRI data demonstrate a great potential of the proposed technique for routine clinical use.
authors.affiliation: Huaxi MR Research Center, Sichuan University, Chengdu, Sichuan 610065, China; College of Computer Science, Sichuan University, Chengdu, Sichuan 610065, China; and Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee 37232-2310.
authors.forename: Xi
authors.initials: X
authors.lastname: Wu
authors.forename: Shujuan
authors.initials: S
authors.lastname: Liu
authors.forename: Min
authors.initials: M
authors.lastname: Wu
authors.forename: Huaiqiang
authors.initials: H
authors.lastname: Sun
authors.forename: Jiliu
authors.initials: J
authors.lastname: Zhou
authors.forename: Qiyong
authors.initials: Q
authors.lastname: Gong
authors.forename: Zhaohua
authors.initials: Z
authors.lastname: Ding
mesh_terms: D000465:Algorithms; D016880:Anisotropy; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*